‌Paul Madley Dowd

What motivated you to come to Bristol and do this programme?

There were a few reasons that lead me to choose to begin my PhD in the School of Social and Community Medicine. The first was the reputation that the department held within the academic community. Correspondence with dissertation supervisors and tutors at other universities lead me to the conclusion that the SSCM houses a strong team of researchers working on novel epidemiological methods. I was also drawn by the project offered which focussed on Psychiatric Epidemiology. This provided me an interesting opportunity to combine the skills I developed during my prior BSc in Psychology and MSc in Statistics. Finally this was an exciting chance for me to return to Bristol. I completed my undergraduate degree here in Bristol in 2013. I had 3 years away which allowed me to reflect on what a great city Bristol is to live in.

What is the key research question of your PhD research project and what have you found out so far?

My main PhD project is titled “A causal analysis of maternal substance use during pregnancy and offspring psychopathology”. A motivation for this research goes as follows: According to Statistics on Smoking, England 2015, 1 in 9 pregnant mothers in England are current smokers. There were nearly 700,000 live births in England and Wales in 2015. Assuming the prevalence of maternal smoking during pregnancy is constant across the UK, if a causal link is present this would mean that approximately 78,000 individuals born each year are being put at greater risk of developing psychopathological outcomes. It is my hope that my research will contribute to behaviour change, potentially reducing the proportion of individuals smoking during pregnancy. Both traditional and novel epidemiological investigations will be performed in order to attempt to unravel the confounding associated with substance use and mental health outcomes.

I am currently working on mini projects in the first year of my PhD. The first is a simulation study with a focus on missing data. Reviewers commonly flag issues if the proportion of missing data in the outcome variable is greater than 50%. I am simulating datasets with varying amounts of missing values in the outcome variable and using Multivariate Imputation using Chained Equations (MICE) to impute the missing values. Imputation models containing different combinations of auxiliary variables (variables predictive of the outcome variable and/or missingness but which are not included in the analysis model) are then assessed at these different levels of missingness. It is hoped that this work will inform us whether the cut-off point for outcome missingness cited by reviewers is justified. My second mini project will use Mendelian Randomization to investigate a potential link between maternal vitamin D deficiency during pregnancy and autism outcomes for the offspring (see Cannell’s 2008 review in Medical Hypotheses for an overview of the varied evidence suggesting a potential link). I have yet to decide on my final mini project.

Where do you think your research could lead and what are your future career plans now?

I plan to follow up my PhD with a career in academia, likely within the field of Psychiatric Epidemiology. It is early days but I hope my work here will provide a strong foundation to allow me to achieve this goal.